Ionizable amino lipid interactions with POPC: implications for lipid nanoparticle function
Bibliographic record
Abstract
Lipid nanoparticles (LNPs) composed of ionizable cationic lipids are currently the leading systems for siRNA delivery in liver disease, with the major limitation of low siRNA release efficacy into the cytoplasm. Ionizable cationic lipids are known to be of critical importance in LNP structure and stability, siRNA entrapment, and endosomal disruption. However, their distribution inside the LNPs and their exact role in cytoplasmic delivery remain unclear. A recent study [Kulkarni et al., On the formation and morphology of lipid nanoparticles containing ionizable cationic lipids and siRNA, ACS Nano, 2018, 12(5), 4787-4795] on LNP-siRNA systems containing the ionizable lipid DLin-KC2-DMA (also known as KC2 with an apparent pKa of ca. 6.7) suggested that neutral KC2 segregates from other components and forms an amorphous oil droplet in the core of LNPs. In this paper, we present evidence supporting the model proposed by Kulkarni et al. We studied KC2 segregation in the presence of POPC using molecular dynamics simulation, deuterium NMR, SAXS, and cryo-TEM experiments, and found that neutral KC2 has a high tendency to separate from POPC dispersions. KC2 confinement, upon raising the pH during the formulation process, could result in rearrangement of the internal structure of LNPs. As interactions between cationic KC2 and anionic endosomal lipids are thought to be a key factor in cargo release, KC2 confinement inside the LNP may be responsible for the observed low release efficacy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".